Users know what they like and dislike about an enterprise's products or services, and users know why they continue to use or purchase services or products offered by an enterprise. A user can be any individual or organization that uses or purchases services, items, or products offered for use or sale by an enterprise. Enterprises refer to the knowledge of how a user perceives the services, items, or products they provide as user feedback. User feedback regarding certain services or products can be obtained directly from a user's answers to survey questions or user feedback can be gleaned indirectly by tracking a user's behavior. Enterprises recognize that incorporation of user feedback may greatly enhance an enterprise's understanding of user challenges and amplify the ability of an enterprise to target services or products to particular users. As a result, most enterprises that sell services or products, consider collecting and assessing user feedback to be a crucial aspect of increasing sales by developing and targeting services or products to individual users. Enterprises typically use computational recommender engines in an attempt to predict a user's preference for a particular service, item, or product. However, typical recommender engines target only optimal personalized recommendation generation for a network of diverse users in item/social element preferences based on the user's common past behavioral patterns or on the service, item, or product characteristics in order to recommend services, items, or products with similar properties. Enterprises and other entities that offer services or products to users continue to seek efficient and reliable input to recommendation engines in order to better assess user feedback and predict user preferences for the services or products they offer to users.